Abnormal brain networks in Meiges syndrome based on centrality analysis and functional network connectivity: a cross-sectional analysis

Yifei Wang, Aocai Yang, Zeyu Song, Yu Chen, Guolin Ma*, Xiaoying Tang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Meige's syndrome (MS) is a neurologically disabling disorder characterized by visual impairment, mastication, and swallowing difficulties. Emerging evidence suggests that MS may stem from disturbances in brain networks. However, current literature inadequately probes the centrality and functional connectivity within these networks. Purpose: This study aims to compare the brain networks of MS patients with those of healthy controls (HC). We focus on examining changes in intrinsic connectivity, the significance of nodes within the global brain network, and functional network connectivity (FNC). Additionally, we seek to identify potential correlations between neuroimaging findings and clinical scales. Method: In this cross-sectional study, we employed centrality analysis and mediation analysis of brain networks using resting-state fMRI data. Voxel-level degree centrality (DC) and eigenvector centrality (EC) served as key features. Independent component analysis was utilized to assess functional connectivity at the network level. Results: Analyses of EC and DC identified abnormal areas in MS patients predominantly in the right thalamus, left middle occipital gyrus, and Cerebellum Inferior. Mediation analysis indicated that disease severity and course of disease are fully mediated by DC values in the right cerebellum. FNC results highlighted abnormal connections in cerebellar-subcortical, memory retrieval-cingulo-opercular task control, and ventral attention-sensory/somatomotor hand networks in MS patients. Conclusions: Our findings reveal multiple abnormalities in centrality and functional connectivity of brain networks in MS patients. Notably, disease severity correlates with alterations in these, potentially influencing disease progression.

Original languageEnglish
JournalBrain Imaging and Behavior
DOIs
Publication statusAccepted/In press - 2025
Externally publishedYes

Keywords

  • Brain network
  • Degree centrality
  • Eigenvector centrality
  • Functional magnetic resonance imaging (fMRI)
  • Functional network connectivity
  • Meige’s syndrome

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